首页> 外文期刊>European Journal of Agronomy >Application of the CSM-CERES-maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment.
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Application of the CSM-CERES-maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment.

机译:CSM-CERES-玉米模型在亚热带环境下淡季玉米种植日期评估和产量预报中的应用。

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In recent years, maize has become one of the main alternative crops for the Autumn-Winter growing season (off-season) in several regions of Brazil. Water deficits, sub-optimum temperatures and low solar radiation levels are some of the more common problems that are experienced during this growing season. However, the impact of variable weather conditions on crop production can be analyzed with crop simulation models. The objectives of this study were to evaluate the Cropping System Model (CSM)-CERES-Maize for its ability to simulate growth, development, grain yield for four different maturity maize hybrids grown off-season in a subtropical region of Brazil, to study the impact of different planting dates on maize performance under rainfed and irrigated conditions, and for yield forecasting for the most common off-season production system. The CSM-CERES-Maize model was evaluated with experimental data collected during three field experiments conducted in Piracicaba, SP, Brazil. The experiments were completely randomized with three replications for the 2001 experiment and four replications for the 2002 experiments. For the yield forecasting application, daily weather data for 2002 were used until the forecast date, complemented with 25 years of historical daily weather data for the remainder of the growing season. Six planting dates were simulated, starting on February 1 and repeated every 15 days until April 15. The evaluation of the CSM-CERES-Maize showed that the model was able to simulate phenology and grain yield for the four hybrids accurately, with normalized RMSE (expressed in percentage) less than 15%. The planting date analysis showed that a delayed planting date from February 1 to April 15 caused a decrease in average yield of 55% for the rainfed and 21% for the irrigated conditions for all hybrids. The yield forecasting analysis demonstrated that an accurate yield forecast could be provided at approximately 45 days prior to the harvest date for all four maize hybrids. These results are promising for farmers and decision makers, as they could have access to accurate yield forecasts prior to final harvest. However, to be able to make practical decisions for stock management of maize grains, it is necessary to develop this methodology for different locations. Future model evaluations might also be needed due to the release of new cultivars by breeders.
机译:近年来,玉米已成为巴西一些地区秋冬生长季节(淡季)的主要替代作物之一。缺水,最适温度和较低的太阳辐射水平是这个生长季节遇到的一些较常见的问题。但是,可以使用作物模拟模型来分析天气变化对作物生产的影响。这项研究的目的是评估种植系统模型(CSM)-CERES-玉米在巴西亚热带地区淡季生长的四种不同成熟度玉米杂交种的生长,发育和籽粒产量的模拟能力,以研究其在雨育和灌溉条件下,不同播种日期对玉米性能的影响,以及最常见的淡季生产系统的产量预测。 CSM-CERES-玉米模型是通过在巴西SP Raracicaba进行的三个田间实验收集的实验数据进行评估的。实验完全随机化,其中2001年实验重复3次,2002年实验重复4次。对于单产预报应用,使用了直到预报日期为止的2002年每日天气数据,并补充了生长季剩余时间中25年的历史每日天气数据。模拟了6个播种日期,从2月1日开始,每15天重复一次,直到4月15日。对CSM-CERES-玉米的评估表明,该模型能够准确地模拟这四个杂种的物候和籽粒产量,并使用归一化RMSE(小于15%。播种期分析表明,从2月1日到4月15日播种期推迟,所有杂交种的雨育平均产量降低55%,灌溉条件下平均产量降低21%。产量预测分析表明,所有四种玉米杂交种在收获日期前约45天均可提供准确的产量预测。这些结果对于农民和决策者来说是有希望的,因为他们可以在最终收获之前获得准确的产量预测。但是,为了能够对玉米谷物的库存管理做出切实可行的决策,有必要针对不同地点开发这种方法。由于育种者释放了新品种,未来可能还需要模型评估。

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